The Dark Arts of Web Automation
Ominous, right?
Ominous, right?
Yohan Lasorsa, Developer Advocate at Microsoft, and Olivier Leplus, Developer Advocate at AWS, opened their joint talk with a premise most web developers already accept: AI helps you build websites. Their argument is that the reverse is now equally true -- the web is becoming AI's runtime, its data source, and …
Sandipan Bhaumik (LinkedIn), Data & AI Tech Lead at Databricks, opened with an anecdote that set the tone for the whole talk. A single credit-scoring agent ran for two weeks in production without issues. The team added four more agents. Within days, 20% of risk ratings were wrong -- not because the …
Sonny Merla, Mauro Luchetti, and Mattia Redaelli (Quantyca) opened with a question that any large organization experimenting with AI agents will recognize: what happens when dozens of teams across multiple continents are all building agents independently?
Juan Herreros Elorza (LinkedIn, GitHub), Team Lead on the Cloud Native Technology team at Banking Circle, makes a deceptively simple argument: the platform engineering practices that have always been "best practices" are now prerequisites. Not because they've changed, but because AI coding agents have become first-class users of internal developer …
Tun Shwe (LinkedIn) and Jeremy Frenay (LinkedIn), both AI Engineers at Lenses.io, gave a joint talk at AI Engineer Europe 2026 on what happens when MCP servers leave the safety of a developer's laptop. Their central claim: most MCP servers are built for single-player local development and collapse the …
Nimrod Hauser (LinkedIn, X), a founding engineer at Baz, opened his talk at AI Engineer Europe with a deceptively simple observation: public MCP servers ship tools designed for everyone, which means they're optimized for no one. When you plug generic tools into a production agent, the agent hallucinates URLs, saves …
A post making the rounds claims that Claude Code subagents share a prompt cache, making parallelism "basically free." It says you can spin up five agents and pay barely more than one. It lists three execution models — fork, teammate, and worktree — and says they all share the cache. Analysis of …
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